Template-matching based object recognition may be employed for many purposes, such as inspection or picking in factory automation (FA), robot vision, security cameras, and the like. The basic processing in template matching involves preliminarily registering a model of the object for recognition (i.e., a template), and evaluating the degree of similarity between the image features in an input image and the model to thereby detect the 2D position or 2D pose of an object included in the input image.
Recently, there has been increasing focus on applying image template matching techniques to recognizing the position or the pose of an object in three dimensions. Template matching may use an existing imaging device without needing a high-quality distance sensor and is thus less costly. However, attempting to recognize an object in any pose through image template matching requires preparing individual templates for each pose to be recognized and iterating through the templates to find a match, so this technique is quite costly in terms of the processing time.
Patent Document 1 discloses a means for countering this problem. More specifically, the views (viewpoints) that appear similar based on the similarity scores for a 2D image projection are grouped to reduce the number of templates. The process is repeated for the reduced number of templates while decreasing the resolutions thereof to create multi-layered templates. However, it is likely that the number of templates cannot be suitably reduced depending on the shape of the recognition object since the technique in Patent Document 1 reduces the number of viewpoints. For instance, symmetrical or simply shaped objects appear similar even when the viewpoints are actually distant. However, the technique in Patent Document 1 is limited because the technique cannot group distant viewpoints; consequently, the technique cannot sufficiently reduce the number of times template matching is performed or reduce the processing time.